Research
DataEI covers six capability categories, each defined by the kind of leverage it creates. Every area is researched the same way — the C.A.S.E. method, end to end — and every area carries its own dataset, its own 0–5 adoption rubric, and its own pipeline. Pick an area to see what we track, what the data shows so far, and what publishes next.
Illustrative sample — these figures show the structure of the dataset and the form a published finding takes. They are not published findings. Sourced figures publish with the report, each carrying an openable source. Read our research integrity policy →
What We Cover
These are the coverage buckets we benchmark systematically — and the ones our briefings, insights, and advisory sessions are organized around.
AI Coding & Development Agents
Small engineering teams shipping like large ones — pair programming, code generation, autonomous dev workflows.
“At what point does adding an AI coding agent stop adding output — and what did the teams past that point change about how they work?”
Open coverage area →Automation & Workflow Orchestration
Automated workflows and integration replacing multi-person ops teams. iPaaS, orchestration, RPA-evolved platforms.
“Which automated workflows survive contact with a process change — and which quietly rot into manual work nobody reports?”
Open coverage area →Operations & Coordination
One operator coordinating what used to need a program-management layer. Fewer coordinators per contributor.
“How much coordination headcount does a company actually need once the status layer maintains itself?”
Open coverage area →Development & Data Infrastructure
Compute, data, observability, and deployment that let a small team run production-grade systems without an SRE org.
“What does it now cost — in people, not dollars — to run production-grade infrastructure at small scale?”
Open coverage area →GTM & Sales Leverage
AI-augmented prospecting, outbound, and RevOps. Revenue per salesperson and headcount-to-pipeline ratios.
“Does AI-augmented go-to-market raise revenue per seller, or only raise activity per seller?”
Open coverage area →Knowledge, Content & Customer Experience
Content, support, and CX produced at large-org volume by small teams through AI synthesis and CX automation.
“What does automated volume do to the outcome the content or support function was actually hired to produce?”
Open coverage area →One Method, Six Areas
Coverage areas differ in what they measure. They do not differ in how they are researched. C.A.S.E. runs end to end in all six, with the same human-and-machine split at every stage — and each area page shows exactly what each stage does there.
Agents watch the sources for every area nightly — filings, pricing pages, release notes, job postings, partner directories, changelogs. No value enters a DataEI dataset without a source passage a client can open.
Every claim is correlated against independent sources. Conflicts, outliers, and figures with no disclosed baseline are flagged and adjudicated by an analyst. Nothing is averaged away to make a chart look clean.
The analyst decides what the evidence means. Each area produces a market landscape, a benchmark cut into the Leverage Index, and research notes — including the findings vendors have no incentive to publish.
Briefings, inquiry, and advisory delivered by the analyst who did the research, with confidence levels, open questions, and the limits of the work stated out loud.
The full method, the Leverage Index inputs, and the weighting are published at /methodology.
Research Agenda
Everything currently in collection or drafting across the six areas, with its status stated. Dates are target publication, and we move them in public rather than quietly.
Need research in one of these areas?
Ask about a market we cover, commission research on a question we do not cover yet, or book an inquiry on a live decision. You work directly with the analyst doing the research.